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Description

Forest Attributes in Washington State.

A small subset of plots in Washington State are sampled and assessed "on-the-ground" as forested or non-forested by the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program, but the FIA also has access to remotely sensed data for all land in the state. The 'forested' package contains a data frame by the same name intended for use in predictive modeling applications where the more easily-accessible remotely sensed data can be used to predict whether a plot is forested or non-forested.

forested forested website

R-CMD-check CRANstatus

Data on Forest Attributes in Washington State

The U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program provides all sorts of estimates of forest attributes for uses in research, legislation, and land management. The FIA uses a set of criteria to classify a plot of land as “forested” or “non-forested,” and that classification is a central data point in many decision-making contexts. A small subset of plots in Washington State are sampled and assessed “on-the-ground” as forested or non-forested, but the FIA has access to remotely sensed data for all land in the state. forested is an R data package containing a data frame, forested, from which we can develop a model on the more easily-accessible remotely sensed data to predict whether a plot is forested or non-forested.

Installation

Install the most recent release of forested from CRAN with:

install.packages("forested")

Install the development version of forested from GitHub with:

# install.packages("pak")
pak::pak("simonpcouch/forested")

Example

library(tibble)
library(forested)

forested
#> # A tibble: 7,107 × 19
#>    forested  year elevation eastness northness roughness tree_no_tree dew_temp
#>    <fct>    <dbl>     <dbl>    <dbl>     <dbl>     <dbl> <fct>           <dbl>
#>  1 Yes       2005       881       90        43        63 Tree             0.04
#>  2 Yes       2005       113      -25        96        30 Tree             6.4 
#>  3 No        2005       164      -84        53        13 Tree             6.06
#>  4 Yes       2005       299       93        34         6 No tree          4.43
#>  5 Yes       2005       806       47       -88        35 Tree             1.06
#>  6 Yes       2005       736      -27       -96        53 Tree             1.35
#>  7 Yes       2005       636      -48        87         3 No tree          1.42
#>  8 Yes       2005       224      -65       -75         9 Tree             6.39
#>  9 Yes       2005        52      -62        78        42 Tree             6.5 
#> 10 Yes       2005      2240      -67       -74        99 No tree         -5.63
#> # ℹ 7,097 more rows
#> # ℹ 11 more variables: precip_annual <dbl>, temp_annual_mean <dbl>,
#> #   temp_annual_min <dbl>, temp_annual_max <dbl>, temp_january_min <dbl>,
#> #   vapor_min <dbl>, vapor_max <dbl>, canopy_cover <dbl>, lon <dbl>, lat <dbl>,
#> #   land_type <fct>
Metadata

Version

0.1.0

License

Unknown

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